Senior Software Engineer, Applied Analytics

General Motors•Austin, TX

36d•$134,000 - $226,000•Hybrid

About The Position

Senior Software Engineer, Applied Analytics Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to the Technical/Innovation Center in Warren (MI), Austin (TX), or Mountain View (CA) three times per week, at minimum. This position can be located at any of these locations. Why Join Us General Motors is at the forefront of transforming transportation through software-driven innovation. We're driven by our bold vision of a future with Zero Crashes, Zero Emissions, and Zero Congestion. As we push forward into an era of vehicle intelligence and digital engineering, Artificial Intelligence and Data Science are a cornerstone of our strategy. Join a team at the forefront of innovation, where vehicle software design, release, warranty, and telemetry data converge to transform engineering and quality processes. We're pioneering intelligent automation through advanced prognostics powered by smart algorithms, large language models (LLMs), and machine learning driving faster issue resolution and launching vehicles with exceptional quality. We're looking for a Senior Software Engineer to build data pipelines, deploy scalable, AI-driven solutions, create interactive web apps that deliver measurable impact across vehicle engineering and customer experience. The Role As a Senior Software Engineer, you'll lead the deployment of scalable AI/ML powered analytics and prognostics applications in a cloud environment, driving innovation across vehicle telemetry and software integration domains. You'll collaborate cross-functionally with engineers, data scientists, and domain experts to deliver high-impact solutions that improve vehicle quality and customer satisfaction. You will contribute to executive decision-making, product launch strategies, and data-driven quality improvements while staying ahead in a fast-paced, evolving tech landscape.

Requirements

Bachelor's degree (or equivalent work experience) in Computer Science, Data Science, or a related field.
Minimum of 5 years of hands-on experience delivering enterprise-scale software products
Experience with visualization tools (Power BI) and libraries (D3.js, Plotly), interactive web apps (Databricks apps, Azure Apps)
Advanced proficiency in both front-end development (React, Angular, TypeScript, HTML/CSS) and back-end development (Node.js, Python).
Deep understanding of hybrid-cloud and cloud-native software architecture, system design, and security, including microservices and containerization using Azure, Azure Key Vault, App Services, and Azure Kubernetes Services (or similar cloud platforms).
Experience with CI/CD processes, including automated builds, deployments, and pipeline development.
Familiarity with data science use cases and machine learning development lifecycle.
Exceptional analytical and independent problem-solving capabilities
Strong listening and communication skills and ability to collaborate cross-functionally.
Proven ability to lead engineering projects, mentor early-career developers, and collaborate effectively with data scientists, product managers, and non-technical stakeholders.

Nice To Haves

Experience with developing and deploying data pipelines
Experience with Databricks Delta Lake, Mlflow, Unity Catalog.
Experience integrating machine learning models and Databricks workflows.

Responsibilities

Collaborate with data scientists, and stakeholders to deliver applications that train and serve machine learning models and create apps that make large datasets available to wider audience
Lead front-end and back-end software architecture, design, and development ensuring alignment with GM technology and security standards.
Implement software validation, testing, code review, documentation, and production monitoring processes to ensure user satisfaction, quality, and supportability.
Work with partner teams such as data governance, infrastructure, architecture, and operations on platform management and technology migrations as required.
Keep up with new trends and technologies and actively seek ways to increase productivity, including using GenAI where appropriate.
Encourage continuous learning, knowledge sharing, and development within the team and the broader software engineering community.

Benefits

GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
This job may be eligible for relocation benefits.
Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

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